Niki Kilbertus

74 papers A* 18A 2C 1Journal 47Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Conservative Continuous-Time Treatment Optimization. CoRR Nora Schneider, Georg Manten, Niki Kilbertus
2025	J	`jnl`	An Analysis of Causal Effect Estimation using Outcome Invariant Data Augmentation. CoRR Uzair Akbar, Niki Kilbertus, Hao Shen, Krikamol Muandet, Bo Dai
2025	—	`conf`	An Asymmetric Independence Model for Causal Discovery on Path Spaces. CLeaR Georg Manten, Cecilia Casolo, Søren Wengel Mogensen, Niki Kilbertus
2025	J	`jnl`	An Asymmetric Independence Model for Causal Discovery on Path Spaces. CoRR Georg Manten, Cecilia Casolo, Søren Wengel Mogensen, Niki Kilbertus
2025	J	`jnl`	Cluster-Dags as Powerful Background Knowledge For Causal Discovery. CoRR Jan Marco Ruiz de Vargas, Kirtan Padh, Niki Kilbertus
2025	A*	`conf`	Generative Intervention Models for Causal Perturbation Modeling. ICML Nora Schneider, Lars Lorch, Niki Kilbertus, Bernhard Schölkopf, Andreas Krause
2025	J	`jnl`	Graph Distance Based on Cause-Effect Estimands with Latents. CoRR Zhufeng Li, Niki Kilbertus
2025	J	`jnl`	Identifiability Challenges in Sparse Linear Ordinary Differential Equations. CoRR Cecilia Casolo, Sören Becker, Niki Kilbertus
2025	A*	`conf`	Learning Representations of Instruments for Partial Identification of Treatment Effects. ICML Jonas Schweisthal, Dennis Frauen, Maresa Schröder, Konstantin Hess, Niki Kilbertus, Stefan Feuerriegel
2025	J	`jnl`	Predicting symbolic ODEs from multiple trajectories. CoRR Yakup Emre Sahin, Niki Kilbertus, Sören Becker
2025	A*	`conf`	Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes. ICLR Georg Manten, Cecilia Casolo, Emilio Ferrucci, Søren Wengel Mogensen, Cristopher Salvi, Niki Kilbertus
2025	A*	`conf`	Whole Genome Transformer for Gene Interaction Effects in Microbiome Habitat Specificity. AAAI Zhufeng Li, Sandeep Suresh Cranganore, Nicholas D. Youngblut, Niki Kilbertus
2025	—	`conf`	Your Assumed DAG is Wrong And Here's How To Deal With It. CLeaR Kirtan Padh, Zhufeng Li, Cecilia Casolo, Niki Kilbertus
2025	J	`jnl`	Your Assumed DAG is Wrong and Here's How To Deal With It. CoRR Kirtan Padh, Zhufeng Li, Cecilia Casolo, Niki Kilbertus
2024	J	`jnl`	Causal machine learning for predicting treatment outcomes. CoRR Stefan Feuerriegel, Dennis Frauen, Valentyn Melnychuk, Jonas Schweisthal, Konstantin Hess, Alicia Curth, Stefan Bauer, Niki Kilbertus, Isaac S. Kohane, Mihaela van der Schaar
2024	J	`jnl`	Generative Intervention Models for Causal Perturbation Modeling. CoRR Nora Schneider, Lars Lorch, Niki Kilbertus, Bernhard Schölkopf, Andreas Krause
2024	J	`jnl`	Learning Counterfactually Invariant Predictors. Trans. Mach. Learn. Res. Francesco Quinzan, Cecilia Casolo, Krikamol Muandet, Yucen Luo, Niki Kilbertus
2024	J	`jnl`	Learning Representations of Instruments for Partial Identification of Treatment Effects. CoRR Jonas Schweisthal, Dennis Frauen, Maresa Schröder, Konstantin Hess, Niki Kilbertus, Stefan Feuerriegel
2024	A*	`conf`	ODEFormer: Symbolic Regression of Dynamical Systems with Transformers. ICLR Stéphane d'Ascoli, Sören Becker, Philippe Schwaller, Alexander Mathis, Niki Kilbertus
2024	J	`jnl`	Projected Neural Differential Equations for Learning Constrained Dynamics. CoRR Alistair White, Anna Büttner, Maximilian Gelbrecht, Valentin Duruisseaux, Niki Kilbertus, Frank Hellmann, Niklas Boers
2024	J	`jnl`	Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes. CoRR Georg Manten, Cecilia Casolo, Emilio Ferrucci, Søren Wengel Mogensen, Cristopher Salvi, Niki Kilbertus
2024	A*	`conf`	Targeted Sequential Indirect Experiment Design. NeurIPS Elisabeth Ailer, Niclas Dern, Jason S. Hartford, Niki Kilbertus
2024	J	`jnl`	Targeted Sequential Indirect Experiment Design. CoRR Elisabeth Ailer, Niclas Dern, Jason S. Hartford, Niki Kilbertus
2024	C	`conf`	Towards Physically Consistent Deep Learning For Climate Model Parameterizations. ICMLA Birgit Kühbacher, Fernando Iglesias-Suarez, Niki Kilbertus, Veronika Eyring
2024	J	`jnl`	Towards Physically Consistent Deep Learning For Climate Model Parameterizations. CoRR Birgit Kühbacher, Fernando Iglesias-Suarez, Niki Kilbertus, Veronika Eyring
2024	A*	`conf`	Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation. ICLR Luca Eyring, Dominik Klein, Théo Uscidda, Giovanni Palla, Niki Kilbertus, Zeynep Akata, Fabian J. Theis
2024	J	`jnl`	Uncertainty-Aware Optimal Treatment Selection for Clinical Time Series. CoRR Thomas Schwarz, Cecilia Casolo, Niki Kilbertus
2024	J	`jnl`	Whole Genome Transformer for Gene Interaction Effects in Microbiome Habitat Specificity. CoRR Zhufeng Li, Sandeep Suresh Cranganore, Nicholas D. Youngblut, Niki Kilbertus
2023	A*	`conf`	Modeling content creator incentives on algorithm-curated platforms. ICLR Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus, Sarah Dean
2023	J	`jnl`	ODEFormer: Symbolic Regression of Dynamical Systems with Transformers. CoRR Stéphane d'Ascoli, Sören Becker, Alexander Mathis, Philippe Schwaller, Niki Kilbertus
2023	A*	`conf`	Predicting Ordinary Differential Equations with Transformers. ICML Sören Becker, Michal Klein, Alexander Neitz, Giambattista Parascandolo, Niki Kilbertus
2023	J	`jnl`	Predicting Ordinary Differential Equations with Transformers. CoRR Sören Becker, Michal Klein, Alexander Neitz, Giambattista Parascandolo, Niki Kilbertus
2023	A*	`conf`	Sequential Underspecified Instrument Selection for Cause-Effect Estimation. ICML Elisabeth Ailer, Jason S. Hartford, Niki Kilbertus
2023	J	`jnl`	Sequential Underspecified Instrument Selection for Cause-Effect Estimation. CoRR Elisabeth Ailer, Jason S. Hartford, Niki Kilbertus
2023	J	`jnl`	Stabilized Neural Differential Equations for Learning Constrained Dynamics. CoRR Alistair White, Niki Kilbertus, Maximilian Gelbrecht, Niklas Boers
2023	A*	`conf`	Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints. NeurIPS Alistair White, Niki Kilbertus, Maximilian Gelbrecht, Niklas Boers
2023	—	`conf`	Stochastic Causal Programming for Bounding Treatment Effects. CLeaR Kirtan Padh, Jakob Zeitler, David S. Watson, Matt J. Kusner, Ricardo Silva, Niki Kilbertus
2023	J	`jnl`	Supervised learning and model analysis with compositional data. PLoS Comput. Biol. Shimeng Huang, Elisabeth Ailer, Niki Kilbertus, Niklas Pfister
2023	J	`jnl`	Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation. CoRR Luca Eyring, Dominik Klein, Théo Uscidda, Giovanni Palla, Niki Kilbertus, Zeynep Akata, Fabian J. Theis
2022	J	`jnl`	Discovering ordinary differential equations that govern time-series. CoRR Sören Becker, Michal Klein, Alexander Neitz, Giambattista Parascandolo, Niki Kilbertus
2022	J	`jnl`	Learning Counterfactually Invariant Predictors. CoRR Francesco Quinzan, Cecilia Casolo, Krikamol Muandet, Niki Kilbertus, Yucen Luo
2022	J	`jnl`	Modeling Content Creator Incentives on Algorithm-Curated Platforms. CoRR Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus, Sarah Dean
2022	—	`conf`	Multi-disciplinary fairness considerations in machine learning for clinical trials. FAccT Isabel Chien, Nina Deliu, Richard E. Turner, Adrian Weller, Sofia S. Villar, Niki Kilbertus
2022	J	`jnl`	Multi-disciplinary fairness considerations in machine learning for clinical trials. CoRR Isabel Chien, Nina Deliu, Richard E. Turner, Adrian Weller, Sofia S. Villar, Niki Kilbertus
2022	J	`jnl`	Numerical Analysis of the Causal Action Principle in Low Dimensions. CoRR Felix Finster, Robert H. Jonsson, Niki Kilbertus
2022	A*	`conf`	Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution. NeurIPS Leon Hetzel, Simon Böhm, Niki Kilbertus, Stephan Günnemann, Mohammad Lotfollahi, Fabian J. Theis
2022	J	`jnl`	Predicting single-cell perturbation responses for unseen drugs. CoRR Leon Hetzel, Simon Böhm, Niki Kilbertus, Stephan Günnemann, Mohammad Lotfollahi, Fabian J. Theis
2022	A*	`conf`	Sparsity in Continuous-Depth Neural Networks. NeurIPS Hananeh Aliee, Till Richter, Mikhail Solonin, Ignacio Ibarra, Fabian J. Theis, Niki Kilbertus
2022	J	`jnl`	Sparsity in Continuous-Depth Neural Networks. CoRR Hananeh Aliee, Till Richter, Mikhail Solonin, Ignacio Ibarra, Fabian J. Theis, Niki Kilbertus
2022	J	`jnl`	Stochastic Causal Programming for Bounding Treatment Effects. CoRR Kirtan Padh, Jakob Zeitler, David S. Watson, Matt J. Kusner, Ricardo Silva, Niki Kilbertus
2022	J	`jnl`	Supervised Learning and Model Analysis with Compositional Data. CoRR Shimeng Huang, Elisabeth Ailer, Niki Kilbertus, Niklas Pfister
2021	J	`jnl`	A causal view on compositional data. CoRR Elisabeth Ailer, Christian L. Müller, Niki Kilbertus
2021	J	`jnl`	Beyond Predictions in Neural ODEs: Identification and Interventions. CoRR Hananeh Aliee, Fabian J. Theis, Niki Kilbertus
2021	J	`jnl`	Beyond traditional assumptions in fair machine learning. CoRR Niki Kilbertus
2021	A*	`conf`	On Component Interactions in Two-Stage Recommender Systems. NeurIPS Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus
2021	A*	`conf`	On Disentangled Representations Learned from Correlated Data. ICML Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer
2021	J	`jnl`	On component interactions in two-stage recommender systems. CoRR Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus
2020	A*	`conf`	A Class of Algorithms for General Instrumental Variable Models. NeurIPS Niki Kilbertus, Matt J. Kusner, Ricardo Silva
2020	J	`jnl`	A Class of Algorithms for General Instrumental Variable Models. CoRR Niki Kilbertus, Matt J. Kusner, Ricardo Silva
2020	—	`—`	Beyond traditional assumptions in fair machine learning Niki Kilbertus
2020	J	`jnl`	Exploration in two-stage recommender systems. CoRR Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus
2020	A	`conf`	Fair Decisions Despite Imperfect Predictions. AISTATS Niki Kilbertus, Manuel Gomez Rodriguez, Bernhard Schölkopf, Krikamol Muandet, Isabel Valera
2020	J	`jnl`	Is Independence all you need? On the Generalization of Representations Learned from Correlated Data. CoRR Frederik Träuble, Elliot Creager, Niki Kilbertus, Anirudh Goyal, Francesco Locatello, Bernhard Schölkopf, Stefan Bauer
2019	J	`jnl`	Convolutional neural networks: a magic bullet for gravitational-wave detection? CoRR Timothy D. Gebhard, Niki Kilbertus, Ian Harry, Bernhard Schölkopf
2019	J	`jnl`	Improving Consequential Decision Making under Imperfect Predictions. CoRR Niki Kilbertus, Manuel Gomez-Rodriguez, Bernhard Schölkopf, Krikamol Muandet, Isabel Valera
2019	A	`conf`	The Sensitivity of Counterfactual Fairness to Unmeasured Confounding. UAI Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva
2019	J	`jnl`	The Sensitivity of Counterfactual Fairness to Unmeasured Confounding. CoRR Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva
2018	A*	`conf`	Blind Justice: Fairness with Encrypted Sensitive Attributes. ICML Niki Kilbertus, Adrià Gascón, Matt J. Kusner, Michael Veale, Krishna P. Gummadi, Adrian Weller
2018	J	`jnl`	Blind Justice: Fairness with Encrypted Sensitive Attributes. CoRR Niki Kilbertus, Adrià Gascón, Matt J. Kusner, Michael Veale, Krishna P. Gummadi, Adrian Weller
2018	J	`jnl`	Generalization in anti-causal learning. CoRR Niki Kilbertus, Giambattista Parascandolo, Bernhard Schölkopf
2018	A*	`conf`	Learning Independent Causal Mechanisms. ICML Giambattista Parascandolo, Niki Kilbertus, Mateo Rojas-Carulla, Bernhard Schölkopf
2017	—	`conf`	Avoiding Discrimination through Causal Reasoning. NIPS Niki Kilbertus, Mateo Rojas-Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, Bernhard Schölkopf
2017	J	`jnl`	Avoiding Discrimination through Causal Reasoning. CoRR Niki Kilbertus, Mateo Rojas-Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, Bernhard Schölkopf
2017	J	`jnl`	Learning Independent Causal Mechanisms. CoRR Giambattista Parascandolo, Mateo Rojas-Carulla, Niki Kilbertus, Bernhard Schölkopf